Dear list,
I'm trying to fit a mixed-effects model to a problem that includes:
a continuous response variable (mean jumped distance by 17 species of
frogs) in 3 different arenas and under 2 types of stimuli. So, it's a kind
of two-way ANOVA design. I have the species phylogeny and prepared its


I included the following priors:

prior = list(R = list(V = 1, fix = 1), G=list(G1=list(V=1, nu=0.02)))

and the model:

                 random=~Specie, data=df_spe, family="gaussian",
                 ginverse = list(Specie=treeAinv), nodes="ALL",
prior=prior, nitt=300000, burnin=25000, thin = 100, verbose=FALSE)

which seems to converge well (heidel.diag p-value = 0.428), ESS greater
than 1000 for both random and fixed effects.

My question is: how can I incorporate intraspecific variation in the jumped
distance? I have the standard error of the distance and tried to make the
model as:

random=~Species+ us(1+se_distance):Species

but I keep getting an error about prior specification:

Error in MCMCglmm(mean_distance ~ type_arena * type_og_stimulus, random =
~Specie +  :
  prior$G has the wrong number of structures

Thank you in advance,

*Diogo B. Provete, PhD.*
FAPESP Post-doctoral fellow
Department of Environmental Sciences
Centre for Sciences and Technologies for Sustainability
Federal University of São Carlos

Gothenburg Global Biodiversity Centre
Box 462   SE-405 30
Göteborg, Sverige

Cell phone: +5515981022137
Skype: diogoprovete

Editor: Amphibia-Reptilia | Biodiversity Data Journal

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